Antenna Season Report Notebook¶

Josh Dillon, Last Revised January 2022

This notebook examines an individual antenna's performance over a whole season. This notebook parses information from each nightly rtp_summarynotebook (as saved to .csvs) and builds a table describing antenna performance. It also reproduces per-antenna plots from each auto_metrics notebook pertinent to the specific antenna.

In [1]:
import os
from IPython.display import display, HTML
display(HTML("<style>.container { width:100% !important; }</style>"))
In [2]:
# If you want to run this notebook locally, copy the output of the next cell into the next line of this cell.
# antenna = "004"
# csv_folder = '/lustre/aoc/projects/hera/H5C/H5C_Notebooks/_rtp_summary_'
# auto_metrics_folder = '/lustre/aoc/projects/hera/H5C/H5C_Notebooks/auto_metrics_inspect'
# os.environ["ANTENNA"] = antenna
# os.environ["CSV_FOLDER"] = csv_folder
# os.environ["AUTO_METRICS_FOLDER"] = auto_metrics_folder
In [3]:
# Use environment variables to figure out path to the csvs and auto_metrics
antenna = str(int(os.environ["ANTENNA"]))
csv_folder = os.environ["CSV_FOLDER"]
auto_metrics_folder = os.environ["AUTO_METRICS_FOLDER"]
print(f'antenna = "{antenna}"')
print(f'csv_folder = "{csv_folder}"')
print(f'auto_metrics_folder = "{auto_metrics_folder}"')

antenna = "321"
csv_folder = "/home/obs/src/H6C_Notebooks/_rtp_summary_"
auto_metrics_folder = "/home/obs/src/H6C_Notebooks/auto_metrics_inspect"
In [4]:
display(HTML(f'<h1 style=font-size:50px><u>Antenna {antenna} Report</u><p></p></h1>'))

Antenna 321 Report

In [5]:
import numpy as np
import pandas as pd
pd.set_option('display.max_rows', 1000)
import glob
import re
from hera_notebook_templates.utils import status_colors, Antenna
In [6]:
# load csvs and auto_metrics htmls in reverse chronological order
csvs = sorted(glob.glob(os.path.join(csv_folder, 'rtp_summary_table*.csv')))[::-1]
print(f'Found {len(csvs)} csvs in {csv_folder}')
auto_metric_htmls = sorted(glob.glob(auto_metrics_folder + '/auto_metrics_inspect_*.html'))[::-1]
print(f'Found {len(auto_metric_htmls)} auto_metrics notebooks in {auto_metrics_folder}')

Found 33 csvs in /home/obs/src/H6C_Notebooks/_rtp_summary_
Found 31 auto_metrics notebooks in /home/obs/src/H6C_Notebooks/auto_metrics_inspect
In [7]:
# Per-season options
mean_round_modz_cut = 4
dead_cut = 0.4
crossed_cut = 0.0

def jd_to_summary_url(jd):
    return f'https://htmlpreview.github.io/?https://github.com/HERA-Team/H6C_Notebooks/blob/main/_rtp_summary_/rtp_summary_{jd}.html'

def jd_to_auto_metrics_url(jd):
    return f'https://htmlpreview.github.io/?https://github.com/HERA-Team/H6C_Notebooks/blob/main/auto_metrics_inspect/auto_metrics_inspect_{jd}.html'

Load relevant info from summary CSVs¶

In [8]:
this_antenna = None
jds = []

# parse information about antennas and nodes
for csv in csvs:
    df = pd.read_csv(csv)
    for n in range(len(df)):
        # Add this day to the antenna
        row = df.loc[n]
        if isinstance(row['Ant'], str) and '<a href' in row['Ant']:
            antnum = int(row['Ant'].split('</a>')[0].split('>')[-1]) # it's a link, extract antnum
        else:
            antnum = int(row['Ant'])
        if antnum != int(antenna):
            continue
        
        if np.issubdtype(type(row['Node']), np.integer):
            row['Node'] = str(row['Node'])
        if type(row['Node']) == str and row['Node'].isnumeric():
            row['Node'] = 'N' + ('0' if len(row['Node']) == 1 else '') + row['Node']
            
        if this_antenna is None:
            this_antenna = Antenna(row['Ant'], row['Node'])
        jd = [int(s) for s in re.split('_|\.', csv) if s.isdigit()][-1]
        jds.append(jd)
        this_antenna.add_day(jd, row)
        break
In [9]:
# build dataframe
to_show = {'JDs': [f'<a href="{jd_to_summary_url(jd)}" target="_blank">{jd}</a>' for jd in jds]}
to_show['A Priori Status'] = [this_antenna.statuses[jd] for jd in jds]

df = pd.DataFrame(to_show)

# create bar chart columns for flagging percentages:
bar_cols = {}
bar_cols['Auto Metrics Flags'] = [this_antenna.auto_flags[jd] for jd in jds]
bar_cols[f'Dead Fraction in Ant Metrics (Jee)'] = [this_antenna.dead_flags_Jee[jd] for jd in jds]
bar_cols[f'Dead Fraction in Ant Metrics (Jnn)'] = [this_antenna.dead_flags_Jnn[jd] for jd in jds]
bar_cols['Crossed Fraction in Ant Metrics'] = [this_antenna.crossed_flags[jd] for jd in jds]
bar_cols['Flag Fraction Before Redcal'] = [this_antenna.flags_before_redcal[jd] for jd in jds]
bar_cols['Flagged By Redcal chi^2 Fraction'] = [this_antenna.redcal_flags[jd] for jd in jds]
for col in bar_cols:
    df[col] = bar_cols[col]

z_score_cols = {}
z_score_cols['ee Shape Modified Z-Score'] = [this_antenna.ee_shape_zs[jd] for jd in jds]
z_score_cols['nn Shape Modified Z-Score'] = [this_antenna.nn_shape_zs[jd] for jd in jds]
z_score_cols['ee Power Modified Z-Score'] = [this_antenna.ee_power_zs[jd] for jd in jds]
z_score_cols['nn Power Modified Z-Score'] = [this_antenna.nn_power_zs[jd] for jd in jds]
z_score_cols['ee Temporal Variability Modified Z-Score'] = [this_antenna.ee_temp_var_zs[jd] for jd in jds]
z_score_cols['nn Temporal Variability Modified Z-Score'] = [this_antenna.nn_temp_var_zs[jd] for jd in jds]
z_score_cols['ee Temporal Discontinuties Modified Z-Score'] = [this_antenna.ee_temp_discon_zs[jd] for jd in jds]
z_score_cols['nn Temporal Discontinuties Modified Z-Score'] = [this_antenna.nn_temp_discon_zs[jd] for jd in jds]
for col in z_score_cols:
    df[col] = z_score_cols[col]

ant_metrics_cols = {}
ant_metrics_cols['Average Dead Ant Metric (Jee)'] = [this_antenna.Jee_dead_metrics[jd] for jd in jds]
ant_metrics_cols['Average Dead Ant Metric (Jnn)'] = [this_antenna.Jnn_dead_metrics[jd] for jd in jds]
ant_metrics_cols['Average Crossed Ant Metric'] = [this_antenna.crossed_metrics[jd] for jd in jds]
for col in ant_metrics_cols:
    df[col] = ant_metrics_cols[col]

redcal_cols = {}
redcal_cols['Median chi^2 Per Antenna (Jee)'] = [this_antenna.Jee_chisqs[jd] for jd in jds]
redcal_cols['Median chi^2 Per Antenna (Jnn)'] = [this_antenna.Jnn_chisqs[jd] for jd in jds]   
for col in redcal_cols:
    df[col] = redcal_cols[col]

# style dataframe
table = df.style.hide_index()\
          .applymap(lambda val: f'background-color: {status_colors[val]}' if val in status_colors else '', subset=['A Priori Status']) \
          .background_gradient(cmap='viridis', vmax=mean_round_modz_cut * 3, vmin=0, axis=None, subset=list(z_score_cols.keys())) \
          .background_gradient(cmap='bwr_r', vmin=dead_cut-.25, vmax=dead_cut+.25, axis=0, subset=list([col for col in ant_metrics_cols if 'dead' in col.lower()])) \
          .background_gradient(cmap='bwr_r', vmin=crossed_cut-.25, vmax=crossed_cut+.25, axis=0, subset=list([col for col in ant_metrics_cols if 'crossed' in col.lower()])) \
          .background_gradient(cmap='plasma', vmax=4, vmin=1, axis=None, subset=list(redcal_cols.keys())) \
          .applymap(lambda val: 'font-weight: bold' if val < dead_cut else '', subset=list([col for col in ant_metrics_cols if 'dead' in col.lower()])) \
          .applymap(lambda val: 'font-weight: bold' if val < crossed_cut else '', subset=list([col for col in ant_metrics_cols if 'crossed' in col.lower()])) \
          .applymap(lambda val: 'font-weight: bold' if val > mean_round_modz_cut else '', subset=list(z_score_cols.keys())) \
          .applymap(lambda val: 'color: red' if val > mean_round_modz_cut else '', subset=list(z_score_cols.keys())) \
          .bar(subset=list(bar_cols.keys()), vmin=0, vmax=1) \
          .format({col: '{:,.4f}'.format for col in z_score_cols}) \
          .format({col: '{:,.4f}'.format for col in ant_metrics_cols}) \
          .format('{:,.2%}', na_rep='-', subset=list(bar_cols.keys())) \
          .set_table_styles([dict(selector="th",props=[('max-width', f'70pt')])])

Table 1: Per-Night RTP Summary Info For This Atenna¶

This table reproduces each night's row for this antenna from the RTP Summary notebooks. For more info on the columns, see those notebooks, linked in the JD column.

In [10]:
display(HTML(f'<h2>Antenna {antenna}, Node {this_antenna.node}:</h2>'))
HTML(table.render(render_links=True, escape=False))

Antenna 321, Node N02:

Out[10]:
JDs A Priori Status Auto Metrics Flags Dead Fraction in Ant Metrics (Jee) Dead Fraction in Ant Metrics (Jnn) Crossed Fraction in Ant Metrics Flag Fraction Before Redcal Flagged By Redcal chi^2 Fraction ee Shape Modified Z-Score nn Shape Modified Z-Score ee Power Modified Z-Score nn Power Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Discontinuties Modified Z-Score nn Temporal Discontinuties Modified Z-Score Average Dead Ant Metric (Jee) Average Dead Ant Metric (Jnn) Average Crossed Ant Metric Median chi^2 Per Antenna (Jee) Median chi^2 Per Antenna (Jnn)
2459848 not_connected 100.00% 0.00% 0.00% 0.00% 100.00% 0.00% 1.954103 2.128544 17.595440 17.821874 2.898586 4.056885 3.428511 2.540734 0.6295 0.6567 0.3981 0.000000 0.000000
2459847 not_connected 100.00% 0.00% 0.00% 0.00% 100.00% 0.00% 1.699311 1.612115 16.462256 16.560395 2.476489 3.020069 2.048999 1.109195 0.6476 0.5872 0.4578 0.000000 0.000000
2459846 not_connected 100.00% 0.00% 17.09% 0.00% 100.00% 0.00% 6.005300 5.895377 12.930229 13.763592 8.467315 9.359257 0.813141 0.162129 0.7242 0.4564 0.5188 0.000000 0.000000
2459845 not_connected 100.00% 0.00% 0.00% 0.00% 100.00% 0.00% 2.819266 2.551443 22.687271 23.762501 3.086949 2.891921 2.980920 0.586966 0.6238 0.6185 0.4101 0.000000 0.000000
2459844 not_connected 100.00% 0.00% 0.00% 0.00% - - 42.822766 47.696390 144.696703 150.763278 170.160669 144.207910 29.876305 28.551546 0.8671 0.4985 0.6719 nan nan
2459843 not_connected 100.00% 0.55% 0.55% 0.00% 100.00% 0.00% 2.674724 2.422770 10.031245 10.231028 65.820747 72.730582 2.552809 1.247759 0.6436 0.6290 0.4428 0.000000 0.000000
2459839 not_connected 100.00% - - - - - 16.087735 18.765975 164.896625 164.797609 nan nan -29.231224 -30.920487 nan nan nan nan nan
2459838 not_connected 100.00% 100.00% 100.00% 0.00% 100.00% 0.00% 1.104976 0.151704 12.572946 10.842463 7.253006 5.691443 2.216233 2.022968 0.0987 0.0910 0.0447 0.000000 0.000000
2459836 not_connected - 13.43% 43.50% 0.00% - - nan nan nan nan nan nan nan nan 0.5693 0.4285 0.4075 nan nan
2459835 not_connected 100.00% 0.00% 100.00% 0.00% - - 5.075818 5.530325 10.335894 10.098623 33.434045 32.327697 2.630729 3.982438 0.6907 0.3020 0.5764 nan nan
2459833 not_connected 100.00% 0.00% 100.00% 0.00% - - 16.569026 17.815756 43.472183 43.023153 216.321591 207.816508 33.635083 39.869823 0.6848 0.2991 0.5675 nan nan
2459832 not_connected 100.00% 0.00% 94.09% 0.00% 100.00% 0.00% 4.126250 2.283303 10.056158 8.859412 3.112359 2.169286 2.780778 2.436118 0.7130 0.3283 0.6011 0.000000 0.000000
2459831 not_connected 100.00% 100.00% 100.00% 0.00% - - 4.820387 4.041528 68.382427 67.388992 1.882747 1.217380 -0.743836 -0.900856 0.0295 0.0290 0.0019 nan nan
2459830 not_connected 100.00% 100.00% 100.00% 0.00% 100.00% 0.00% 6.102666 3.744005 14.232045 12.592630 18.721774 14.511878 38.786418 38.576792 0.1035 0.0746 0.0568 0.000000 0.000000
2459829 not_connected 100.00% 100.00% 100.00% 0.00% 100.00% 0.00% 3.340787 1.967578 13.945892 12.424933 13.555295 11.409961 77.904123 77.808417 0.0994 0.0885 0.0420 0.000000 0.000000
2459828 not_connected 100.00% 100.00% 100.00% 0.00% 100.00% 0.00% 6.459457 4.316181 10.954907 9.646944 17.976710 14.725277 64.824058 64.965900 0.0981 0.0738 0.0504 0.000000 0.000000
2459827 not_connected 100.00% 100.00% 100.00% 0.00% 100.00% 0.00% 3.251820 1.779228 17.626571 15.594064 11.350366 9.003641 20.537194 19.632912 0.0993 0.0856 0.0417 0.000000 0.000000
2459826 not_connected 100.00% 100.00% 100.00% 0.00% 100.00% 0.00% 6.308227 4.268597 14.842320 13.395798 24.354757 20.077210 40.622880 40.403155 0.0766 0.0605 0.0319 0.000000 0.000000
2459825 not_connected 100.00% 100.00% 100.00% 0.00% 100.00% 0.00% 6.767937 4.063391 10.949555 9.675501 12.311117 10.128865 5.664368 5.415483 0.0992 0.0699 0.0444 0.000000 0.000000
2459824 not_connected 100.00% 100.00% 100.00% 0.00% 100.00% 0.00% 1.961254 1.082142 14.602352 13.001965 10.001879 10.276851 31.376781 30.798655 0.0960 0.0904 0.0377 0.000000 0.000000
2459823 not_connected 100.00% 100.00% 100.00% 0.00% 100.00% 0.00% nan nan inf inf nan nan nan nan nan nan nan 0.000000 0.000000
2459822 not_connected 100.00% 100.00% 100.00% 0.00% 100.00% 0.00% 42.574037 42.371013 inf inf 3894.529461 3894.148523 5149.357315 5148.737724 nan nan nan 0.000000 0.000000
2459821 not_connected 100.00% 100.00% 100.00% 0.00% 100.00% 0.00% 9.792353 7.958784 13.612914 12.544873 12.118183 9.823380 2.931057 2.935396 0.1009 0.0735 0.0460 0.000000 0.000000
2459820 not_connected 100.00% 0.00% 10.74% 0.00% 100.00% 0.00% 4.655264 2.975713 16.127051 14.313974 33.955889 27.522027 40.986733 40.273796 0.6823 0.5426 0.4621 0.000000 0.000000
2459817 not_connected 100.00% 0.00% 51.08% 0.00% 100.00% 0.00% 9.676300 7.489971 11.189527 10.221069 18.197908 15.506102 6.107616 5.961099 0.6646 0.4069 0.4943 0.000000 0.000000
2459816 not_connected 100.00% 0.00% 18.87% 0.00% 100.00% 0.00% 5.090103 3.815301 15.705513 13.979477 23.914625 21.132749 43.929134 42.633822 0.7900 0.4413 0.6434 0.000000 0.000000
2459815 not_connected 100.00% 0.00% 53.76% 0.00% 100.00% 0.00% 9.005730 7.094535 12.592213 11.528141 22.662342 20.181137 43.392374 43.747550 0.6467 0.4081 0.4888 0.000000 0.000000
2459814 not_connected 0.00% - - - - - nan nan nan nan nan nan nan nan nan nan nan nan nan
2459813 not_connected 100.00% 100.00% 100.00% 0.00% 100.00% 0.00% nan nan inf inf nan nan nan nan nan nan nan 0.000000 0.000000

Load antenna metric spectra and waterfalls from auto_metrics notebooks.¶

In [11]:
htmls_to_display = []
for am_html in auto_metric_htmls:
    html_to_display = ''
    # read html into a list of lines
    with open(am_html) as f:
        lines = f.readlines()
    
    # find section with this antenna's metric plots and add to html_to_display
    jd = [int(s) for s in re.split('_|\.', am_html) if s.isdigit()][-1]
    try:
        section_start_line = lines.index(f'<h2>Antenna {antenna}: {jd}</h2>\n')
    except ValueError:
        continue
    html_to_display += lines[section_start_line].replace(str(jd), f'<a href="{jd_to_auto_metrics_url(jd)}" target="_blank">{jd}</a>')
    for line in lines[section_start_line + 1:]:
        html_to_display += line
        if '<hr' in line:
            htmls_to_display.append(html_to_display)
            break

Figure 1: Antenna autocorrelation metric spectra and waterfalls.¶

These figures are reproduced from auto_metrics notebooks. For more info on the specific plots and metrics, see those notebooks (linked at the JD). The most recent 100 days (at most) are shown.

In [12]:
for i, html_to_display in enumerate(htmls_to_display):
    if i == 100:
        break
    display(HTML(html_to_display))

Antenna 321: 2459848

Ant Node A Priori Status Worst Metric Worst Modified Z-Score nn Shape Modified Z-Score ee Shape Modified Z-Score nn Power Modified Z-Score ee Power Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Discontinuties Modified Z-Score ee Temporal Discontinuties Modified Z-Score
321 N02 not_connected nn Power 17.821874 2.128544 1.954103 17.821874 17.595440 4.056885 2.898586 2.540734 3.428511

Antenna 321: 2459847

Ant Node A Priori Status Worst Metric Worst Modified Z-Score nn Shape Modified Z-Score ee Shape Modified Z-Score nn Power Modified Z-Score ee Power Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Discontinuties Modified Z-Score ee Temporal Discontinuties Modified Z-Score
321 N02 not_connected nn Power 16.560395 1.612115 1.699311 16.560395 16.462256 3.020069 2.476489 1.109195 2.048999

Antenna 321: 2459846

Ant Node A Priori Status Worst Metric Worst Modified Z-Score ee Shape Modified Z-Score nn Shape Modified Z-Score ee Power Modified Z-Score nn Power Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Discontinuties Modified Z-Score nn Temporal Discontinuties Modified Z-Score
321 N02 not_connected nn Power 13.763592 6.005300 5.895377 12.930229 13.763592 8.467315 9.359257 0.813141 0.162129

Antenna 321: 2459845

Ant Node A Priori Status Worst Metric Worst Modified Z-Score nn Shape Modified Z-Score ee Shape Modified Z-Score nn Power Modified Z-Score ee Power Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Discontinuties Modified Z-Score ee Temporal Discontinuties Modified Z-Score
321 N02 not_connected nn Power 23.762501 2.551443 2.819266 23.762501 22.687271 2.891921 3.086949 0.586966 2.980920

Antenna 321: 2459844

Ant Node A Priori Status Worst Metric Worst Modified Z-Score ee Shape Modified Z-Score nn Shape Modified Z-Score ee Power Modified Z-Score nn Power Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Discontinuties Modified Z-Score nn Temporal Discontinuties Modified Z-Score
321 N02 not_connected ee Temporal Variability 170.160669 42.822766 47.696390 144.696703 150.763278 170.160669 144.207910 29.876305 28.551546

Antenna 321: 2459843

Ant Node A Priori Status Worst Metric Worst Modified Z-Score nn Shape Modified Z-Score ee Shape Modified Z-Score nn Power Modified Z-Score ee Power Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Discontinuties Modified Z-Score ee Temporal Discontinuties Modified Z-Score
321 N02 not_connected nn Temporal Variability 72.730582 2.422770 2.674724 10.231028 10.031245 72.730582 65.820747 1.247759 2.552809

Antenna 321: 2459839

Ant Node A Priori Status Worst Metric Worst Modified Z-Score nn Shape Modified Z-Score ee Shape Modified Z-Score nn Power Modified Z-Score ee Power Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Discontinuties Modified Z-Score ee Temporal Discontinuties Modified Z-Score
321 N02 not_connected ee Power 164.896625 18.765975 16.087735 164.797609 164.896625 nan nan -30.920487 -29.231224

Antenna 321: 2459838

Ant Node A Priori Status Worst Metric Worst Modified Z-Score nn Shape Modified Z-Score ee Shape Modified Z-Score nn Power Modified Z-Score ee Power Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Discontinuties Modified Z-Score ee Temporal Discontinuties Modified Z-Score
321 N02 not_connected ee Power 12.572946 0.151704 1.104976 10.842463 12.572946 5.691443 7.253006 2.022968 2.216233

Antenna 321: 2459835

Ant Node A Priori Status Worst Metric Worst Modified Z-Score nn Shape Modified Z-Score ee Shape Modified Z-Score nn Power Modified Z-Score ee Power Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Discontinuties Modified Z-Score ee Temporal Discontinuties Modified Z-Score
321 N02 not_connected ee Temporal Variability 33.434045 5.530325 5.075818 10.098623 10.335894 32.327697 33.434045 3.982438 2.630729

Antenna 321: 2459833

Ant Node A Priori Status Worst Metric Worst Modified Z-Score nn Shape Modified Z-Score ee Shape Modified Z-Score nn Power Modified Z-Score ee Power Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Discontinuties Modified Z-Score ee Temporal Discontinuties Modified Z-Score
321 N02 not_connected ee Temporal Variability 216.321591 17.815756 16.569026 43.023153 43.472183 207.816508 216.321591 39.869823 33.635083

Antenna 321: 2459832

Ant Node A Priori Status Worst Metric Worst Modified Z-Score ee Shape Modified Z-Score nn Shape Modified Z-Score ee Power Modified Z-Score nn Power Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Discontinuties Modified Z-Score nn Temporal Discontinuties Modified Z-Score
321 N02 not_connected ee Power 10.056158 4.126250 2.283303 10.056158 8.859412 3.112359 2.169286 2.780778 2.436118

Antenna 321: 2459831

Ant Node A Priori Status Worst Metric Worst Modified Z-Score ee Shape Modified Z-Score nn Shape Modified Z-Score ee Power Modified Z-Score nn Power Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Discontinuties Modified Z-Score nn Temporal Discontinuties Modified Z-Score
321 N02 not_connected ee Power 68.382427 4.820387 4.041528 68.382427 67.388992 1.882747 1.217380 -0.743836 -0.900856

Antenna 321: 2459830

Ant Node A Priori Status Worst Metric Worst Modified Z-Score ee Shape Modified Z-Score nn Shape Modified Z-Score ee Power Modified Z-Score nn Power Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Discontinuties Modified Z-Score nn Temporal Discontinuties Modified Z-Score
321 N02 not_connected ee Temporal Discontinuties 38.786418 6.102666 3.744005 14.232045 12.592630 18.721774 14.511878 38.786418 38.576792

Antenna 321: 2459829

Ant Node A Priori Status Worst Metric Worst Modified Z-Score nn Shape Modified Z-Score ee Shape Modified Z-Score nn Power Modified Z-Score ee Power Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Discontinuties Modified Z-Score ee Temporal Discontinuties Modified Z-Score
321 N02 not_connected ee Temporal Discontinuties 77.904123 1.967578 3.340787 12.424933 13.945892 11.409961 13.555295 77.808417 77.904123

Antenna 321: 2459828

Ant Node A Priori Status Worst Metric Worst Modified Z-Score nn Shape Modified Z-Score ee Shape Modified Z-Score nn Power Modified Z-Score ee Power Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Discontinuties Modified Z-Score ee Temporal Discontinuties Modified Z-Score
321 N02 not_connected nn Temporal Discontinuties 64.965900 4.316181 6.459457 9.646944 10.954907 14.725277 17.976710 64.965900 64.824058

Antenna 321: 2459827

Ant Node A Priori Status Worst Metric Worst Modified Z-Score ee Shape Modified Z-Score nn Shape Modified Z-Score ee Power Modified Z-Score nn Power Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Discontinuties Modified Z-Score nn Temporal Discontinuties Modified Z-Score
321 N02 not_connected ee Temporal Discontinuties 20.537194 3.251820 1.779228 17.626571 15.594064 11.350366 9.003641 20.537194 19.632912

Antenna 321: 2459826

Ant Node A Priori Status Worst Metric Worst Modified Z-Score nn Shape Modified Z-Score ee Shape Modified Z-Score nn Power Modified Z-Score ee Power Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Discontinuties Modified Z-Score ee Temporal Discontinuties Modified Z-Score
321 N02 not_connected ee Temporal Discontinuties 40.622880 4.268597 6.308227 13.395798 14.842320 20.077210 24.354757 40.403155 40.622880

Antenna 321: 2459825

Ant Node A Priori Status Worst Metric Worst Modified Z-Score nn Shape Modified Z-Score ee Shape Modified Z-Score nn Power Modified Z-Score ee Power Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Discontinuties Modified Z-Score ee Temporal Discontinuties Modified Z-Score
321 N02 not_connected ee Temporal Variability 12.311117 4.063391 6.767937 9.675501 10.949555 10.128865 12.311117 5.415483 5.664368

Antenna 321: 2459824

Ant Node A Priori Status Worst Metric Worst Modified Z-Score ee Shape Modified Z-Score nn Shape Modified Z-Score ee Power Modified Z-Score nn Power Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Discontinuties Modified Z-Score nn Temporal Discontinuties Modified Z-Score
321 N02 not_connected ee Temporal Discontinuties 31.376781 1.961254 1.082142 14.602352 13.001965 10.001879 10.276851 31.376781 30.798655

Antenna 321: 2459823

Ant Node A Priori Status Worst Metric Worst Modified Z-Score nn Shape Modified Z-Score ee Shape Modified Z-Score nn Power Modified Z-Score ee Power Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Discontinuties Modified Z-Score ee Temporal Discontinuties Modified Z-Score
321 N02 not_connected nn Shape nan nan nan inf inf nan nan nan nan

Antenna 321: 2459822

Ant Node A Priori Status Worst Metric Worst Modified Z-Score ee Shape Modified Z-Score nn Shape Modified Z-Score ee Power Modified Z-Score nn Power Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Discontinuties Modified Z-Score nn Temporal Discontinuties Modified Z-Score
321 N02 not_connected ee Power inf 42.574037 42.371013 inf inf 3894.529461 3894.148523 5149.357315 5148.737724

Antenna 321: 2459821

Ant Node A Priori Status Worst Metric Worst Modified Z-Score nn Shape Modified Z-Score ee Shape Modified Z-Score nn Power Modified Z-Score ee Power Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Discontinuties Modified Z-Score ee Temporal Discontinuties Modified Z-Score
321 N02 not_connected ee Power 13.612914 7.958784 9.792353 12.544873 13.612914 9.823380 12.118183 2.935396 2.931057

Antenna 321: 2459820

Ant Node A Priori Status Worst Metric Worst Modified Z-Score ee Shape Modified Z-Score nn Shape Modified Z-Score ee Power Modified Z-Score nn Power Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Discontinuties Modified Z-Score nn Temporal Discontinuties Modified Z-Score
321 N02 not_connected ee Temporal Discontinuties 40.986733 4.655264 2.975713 16.127051 14.313974 33.955889 27.522027 40.986733 40.273796

Antenna 321: 2459817

Ant Node A Priori Status Worst Metric Worst Modified Z-Score ee Shape Modified Z-Score nn Shape Modified Z-Score ee Power Modified Z-Score nn Power Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Discontinuties Modified Z-Score nn Temporal Discontinuties Modified Z-Score
321 N02 not_connected ee Temporal Variability 18.197908 9.676300 7.489971 11.189527 10.221069 18.197908 15.506102 6.107616 5.961099

Antenna 321: 2459816

Ant Node A Priori Status Worst Metric Worst Modified Z-Score nn Shape Modified Z-Score ee Shape Modified Z-Score nn Power Modified Z-Score ee Power Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Discontinuties Modified Z-Score ee Temporal Discontinuties Modified Z-Score
321 N02 not_connected ee Temporal Discontinuties 43.929134 3.815301 5.090103 13.979477 15.705513 21.132749 23.914625 42.633822 43.929134

Antenna 321: 2459815

Ant Node A Priori Status Worst Metric Worst Modified Z-Score nn Shape Modified Z-Score ee Shape Modified Z-Score nn Power Modified Z-Score ee Power Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Discontinuties Modified Z-Score ee Temporal Discontinuties Modified Z-Score
321 N02 not_connected nn Temporal Discontinuties 43.747550 7.094535 9.005730 11.528141 12.592213 20.181137 22.662342 43.747550 43.392374

Antenna 321: 2459814

Ant Node A Priori Status Worst Metric Worst Modified Z-Score nn Shape Modified Z-Score ee Shape Modified Z-Score nn Power Modified Z-Score ee Power Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Discontinuties Modified Z-Score ee Temporal Discontinuties Modified Z-Score
321 N02 not_connected nn Shape nan nan nan nan nan nan nan nan nan

Antenna 321: 2459813

Ant Node A Priori Status Worst Metric Worst Modified Z-Score nn Shape Modified Z-Score ee Shape Modified Z-Score nn Power Modified Z-Score ee Power Modified Z-Score nn Temporal Variability Modified Z-Score ee Temporal Variability Modified Z-Score nn Temporal Discontinuties Modified Z-Score ee Temporal Discontinuties Modified Z-Score
321 N02 not_connected nn Shape nan nan nan inf inf nan nan nan nan
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